Existing cortical and retinal visual prostheses produce bionic vision by translating imagery from a head worn video camera into spatial-temporal patterns of electrical stimulation of a patient's visual pathway. The stimuli are usually delivered using multiple electrodes configured as an implanted electrode array. The resulting bionic vision consists of a spatial-temporal pattern of multiple phosphenes, experienced by the patient as visual percepts such as bright spots of light within a visual field.
In general, current limitations of technology and biology mean that the phosphene pattern has limited spatial resolution, poor dynamic range, and is also irregular. Typical properties of irregular phosphene patterns include:                the size of individual phosphenes varies across the visual field, and the variation may not follow any mathematical or algorithmic model;        the spatial separation between the phosphenes varies across the visual field, also without following any mathematical or algorithmic model, including the fusing of multiple phosphenes into a single phosphene or spatial configurations of fewer phosphenes;        the shape of individual phosphenes varies across the visual field, without following any mathematical or algorithmic model;        the intensity of individual phosphenes varies across the visual field, again without following any mathematical or algorithmic model;        a single applied stimulus may result in multiple phosphenes, which may be spread unevenly and/or sparsely across the visual field; and        multiple distinct stimuli may result in the same, or similar, phosphene patterns.        
Many factors contribute to irregularities in phosphene patterns. Clinical trials of retinal implants, and simulations of cortical prostheses, suggest that factors such as electrode failure (dropouts), non-linear effects of the visual system (cortical magnification, visuotopic/cortical maps), irregular spreading of electrical stimulation due to implant site anatomical variations, and surgical inconsistencies in electrode placement, can all add irregularities to a patient's phosphene map. The complex processes involved are not yet fully understood, and it is likely that a number of as-yet unknown factors also contribute.
As a further result of these factors, along with a current lack of robust and accurate models of how stimuli produce phosphenes, a patient's phosphene map is not generally predictable prior to surgical implantation and electrode activation. Practical bionic vision systems therefore require a training/calibration process, in which stimuli are applied systematically in order to produce phosphenes, the location and appearance of which are reported by the patient. In this way, a mapping can be established between stimuli and phosphenes.
The phosphene mapping process may result in inaccurate estimates due to the lack of spatial and visual frames of reference that can be utilised by a vision-impaired patient and a clinician. The patient's phosphene map may therefore benefit from iterative refinement using multiple cycles of repeated measurements and adjustments to produce a better approximation of the true phosphene map of the patient. Furthermore, ongoing biological changes, and/or technical issues such as electrode failure, may require ongoing adjustment of the patient's phosphene map.
The phosphene mapping process may be regarded as an example of a more general problem of mapping regions of a ‘true’ visual field to a generally arbitrary and irregular output image. Other applications in which similar problems may arise include:                Virtual Reality (VR) systems in which the output displays may be irregular due to properties of optical components (e.g. Fresnel lenses, low-cost multiple lens systems) and/or the use of multiple display panels;        Augmented Reality (AR) systems that have irregular displays, such as spatial (projected) AR systems in which imagery may be projected onto irregular surfaces, and see-through and video pass-through AR displays that have irregular displays, or virtual content overlaid on irregular real-world surfaces; and        Visual display systems with pixels of irregular shape, clusters of irregular pixels, or other irregularities, where it is necessary to perform graphics rendering and other processing to accommodate these irregularities.        
In many of these applications, and in particular in image processing systems for prosthetic vision, it is also desirable that processing can be performed not only in a flexible manner, but also in a computationally-efficient manner. Personal and portable items, such as the processing units for prosthetic vision systems, are desirably small, light-weight, and low power consumption. Extended battery life is an extremely important characteristic in the processing unit for a visual prosthesis.
It is, accordingly, an object of the present invention to provide a flexible and efficient image processing method and system which is applicable to arbitrary and irregular output image patterns, and which may be employed in prosthetic vision processing systems, VR systems, AR systems, and other visual display and processing systems.